Tagging Sign Up Emails as Work vs Personal

Say you’re building a B2B product. A lead who signs up with a corporate email is more likely a qualified buyer.

Of course, email type is not the only signal (see our template on Lead Scoring). Once you've baked all your signals into a Lead Score, you can even pull a daily report of Recent Qualified Leads.

Why SQL?

SQL is fast and flexible. You can write a CASE statement in a snap, no data instrumentation or JIRA tickets required.

SQL you can copy / paste

Use this query on any users table ( ⚠️ if your table is massive, filter by created_at).

   when email similar to '%(gmail|yahoo|outlook|hotmail)%' then 'personal' --simplified list
   else 'business'
 end as email_type
from users;

Sample Output:

| id     | first_name | last_name | email                | email_type |
| 538107 | Aaliyah    | Funk      | aaliyah@craftery.com | business   |
| 471400 | Abbey      | Miller    | abbey@weavel.com     | business   |
| 565108 | Cheyenne   | Reilly    | cheyenne@hotmail.com | personal   |
| ...    | ...        | ...       | ...                  | ...        |

Obviously that list of email domains is simplified to make the concept easy. Here’s a full list of domain names that we consider personal (or burner).

To easily paste that list into your query, use delim.co, choose | as the delimiter, and then paste into your query like so:

Try it yourself?

Run this template against our sample database that mirrors real startup data. See the connection credentials, then connect in PopSQL.

Ready for a modern SQL editor?